KULLMAN, Nicholas; FROGER, Aurélien; MENDOZA, Jorge; GOODSON, Justin

doi:10.1287/ijoc.2020.1035

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KULLMAN, Nicholas
Laboratoire d'Informatique Fondamentale et Appliquée de Tours [LIFAT]

FROGER, Aurélien
Reformulations based algorithms for Combinatorial Optimization [Realopt]
Institut de Mathématiques de Bordeaux [IMB]

MENDOZA, Jorge
HEC Montréal [HEC Montréal]

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Ce document a été publié dans

INFORMS Journal on Computing. 2021, vol. 33, n° 4, p. 1277-1283

Institute for Operations Research and the Management Sciences (INFORMS)

Résumé en anglais

Electric vehicles offer a pathway to more sustainable transportation, but their adoption entails new challenges not faced by their petroleum-based counterparts. One of the most challenging tasks in vehicle routing problems addressing these challenges is determining how to make good charging decisions for an electric vehicle traveling a given route. This is known as the fixed route vehicle charging problem. An exact and efficient algorithm for this task exists, but its implementation is sufficiently complex to deter researchers from adopting it. In this work we introduce frvcpy, an open-source Python package implementing this algorithm. Our aim with the package is to make it easier for researchers to solve electric vehicle routing problems, facilitating the development of optimization tools that may ultimately enable the mass adoption of electric vehicles.< Réduire